This model detects if a Danish text is 'subjective' or 'objective'.
Here is an example of how to load the model in PyTorch using the 🤗Transformers library:
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline tokenizer = AutoTokenizer.from_pretrained("pin/analytical") model = AutoModelForSequenceClassification.from_pretrained("pin/analytical") # create 'senda' sentiment analysis pipeline analytical_pipeline = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer) text = "Jeg synes, det er en elendig film" # in English: 'I think, it is a terrible movie' analytical_pipeline(text)
senda model achieves an accuracy of 0.89 and a macro-averaged F1-score of 0.78 on a small test data set, that Alexandra Institute provides. The model can most certainly be improved, and we encourage all NLP-enthusiasts to give it their best shot - you can use the
senda package to do this.
Feel free to contact author Lars Kjeldgaard on email@example.com.
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